阅读说明：本技术 使用希尔伯特变换进行频谱划分以改进频率扫描 (Spectral partitioning using a Hilbert transform to improve frequency scanning ) 是由 R·库玛尔 A·拉久尔卡尔 于 2019-02-28 设计创作，主要内容包括：一种执行无线通信的方法包括：在初始小区搜索期间,由用户设备(UE)在该UE的最大前端带宽上累积接收数据的样本。该方法还包括：将样本分割成较小的不重叠的频谱块,以及对这些较小的不重叠的块中的一个或多个块执行基于相关性的检测。该方法还包括：根据基于相关性的检测的结果来检测无线通信系统。(A method of performing wireless communication comprising: during initial cell search, samples of received data are accumulated by a User Equipment (UE) over a maximum front-end bandwidth of the UE. The method further comprises the following steps: the method includes partitioning samples into smaller non-overlapping blocks of spectrum and performing correlation-based detection on one or more of the smaller non-overlapping blocks. The method further comprises the following steps: the wireless communication system is detected based on a result of the correlation-based detection.)

1. A method of performing wireless communication, the method comprising:

accumulating, by a User Equipment (UE), samples of received data over a maximum front-end bandwidth of the UE during an initial cell search;

partitioning the samples into smaller non-overlapping blocks of spectrum;

performing correlation-based detection on one or more of the smaller non-overlapping blocks; and

detecting a wireless communication system according to a result of the correlation-based detection.

2. The method of claim 1, comprising:

further partitioning at least one of the smaller non-overlapping blocks into smaller non-overlapping blocks.

3. The method of claim 2, comprising:

the spectrum is subdivided in a binary tree manner having a number of levels, wherein at each of the levels, the bandwidth is divided into two halves.

4. The method of claim 3, wherein the subdivision of the bandwidth is achieved by performing a Hilbert transform.

5. The method of claim 3, comprising:

at each of the levels, performing CP correlation detection on each of the smaller non-overlapping blocks.

6. The method of claim 3, comprising:

processing at least one of the two halves by downsampling and rotating the at least one of the two halves.

7. The method of claim 3, comprising:

the number of levels is chosen to ensure that all smallest spectral blocks at the lowest level have a respective bandwidth equal to the minimum supported bandwidth.

8. The method of claim 7, wherein the minimum supported bandwidth is 1.4 MHz.

9. The method of claim 1, comprising:

in response to an inability to make a strong decision on detection of a wireless signal in the sample, the sample is partitioned into two or more smaller non-overlapping blocks.

10. The method of claim 9, comprising:

in response to determining that a strong decision cannot be made for detection of wireless signals in at least one of the smaller non-overlapping blocks, further partitioning the at least one of the smaller non-overlapping blocks into smaller non-overlapping blocks.

11. The method of claim 9, comprising:

determining that a strong decision cannot be made for detection of the wireless signal by determining that z is less than a detection threshold, wherein z is equal to a Cyclic Prefix (CP) accumulation buffer Bcor (n)

12. The method of claim 1, comprising:

in response to detecting a wireless signal in the sample, the sample is partitioned into two or more smaller non-overlapping blocks.

13. The method of claim 12, comprising:

in response to detecting the wireless signal in at least one of the smaller non-overlapping blocks, further partitioning the at least one of the smaller non-overlapping blocks into smaller non-overlapping blocks.

14. The method of claim 12, comprising:

detecting the presence of the wireless signal by determining that z is greater than a detection threshold, wherein z is equal to a Cyclic Prefix (CP) accumulation buffer Bcor (n)

15. The method of claim 12, comprising:

segmenting the samples to accurately locate the wireless communication system of the wireless signal.

16. A wireless communications apparatus, the apparatus comprising:

at least one computer processor; and

at least one memory coupled to the at least one computer processor, wherein the at least one computer processor is configured to:

accumulating, by a User Equipment (UE), samples of received data over a maximum front-end bandwidth of the UE during an initial cell search;

partitioning the samples into smaller non-overlapping blocks of spectrum;

performing correlation-based detection on one or more of the smaller non-overlapping blocks; and

detecting a wireless communication system according to a result of the correlation-based detection.

17. The apparatus of claim 16, wherein the at least one computer processor is configured to: further partitioning at least one of the smaller non-overlapping blocks into smaller non-overlapping blocks.

18. The apparatus of claim 17, wherein the at least one computer processor is configured to: the spectrum is subdivided in a binary tree manner having a number of levels, wherein at each of the levels, the bandwidth is divided into two halves.

19. The apparatus of claim 18, wherein the subdivision of the bandwidth is achieved by performing a hilbert transform.

20. The apparatus of claim 18, wherein the at least one computer processor is configured to: at each of the levels, performing Cyclic Prefix (CP) correlation detection on each of the smaller non-overlapping blocks.

21. The apparatus of claim 18, wherein the at least one computer processor is configured to: processing at least one of the two halves by downsampling and rotating the at least one of the two halves.

22. The apparatus of claim 18, wherein the at least one computer processor is configured to: the number of levels is chosen to ensure that all smallest spectral blocks at the lowest level have a respective bandwidth equal to the minimum supported bandwidth.

23. The apparatus of claim 22, wherein the minimum supported bandwidth is 1.4 MHz.

24. The apparatus of claim 16, wherein the at least one computer processor is configured to: in response to an inability to make a strong decision on detection of a wireless signal in the sample, the sample is partitioned into two or more smaller non-overlapping blocks.

25. The apparatus of claim 24, wherein the at least one computer processor is configured to: in response to determining that a strong decision cannot be made for detection of wireless signals in at least one of the smaller non-overlapping blocks, further partitioning the at least one of the smaller non-overlapping blocks into smaller non-overlapping blocks.

26. The apparatus of claim 24, wherein the at least one computer processor is configured to: determining that none can be paired by determining that z is less than a detection thresholdDetection of line signals makes a strong decision, where z is equal to the Cyclic Prefix (CP) accumulation buffer Bcor (n)

27. The apparatus of claim 16, wherein the at least one computer processor is configured to: in response to detecting a wireless signal in the sample, the sample is partitioned into two or more smaller non-overlapping blocks.

28. The apparatus of claim 27, wherein the at least one computer processor is configured to: in response to detecting the wireless signal in at least one of the smaller non-overlapping blocks, further partitioning the at least one of the smaller non-overlapping blocks into smaller non-overlapping blocks.

29. The apparatus of claim 27, wherein the at least one computer processor is configured to: detecting the presence of the wireless signal by determining that z is greater than a detection threshold, wherein z is equal to a Cyclic Prefix (CP) accumulation buffer Bcor (n)A performance metric of (a).

30. The apparatus of claim 27, wherein the at least one computer processor is configured to: segmenting the samples to accurately locate the wireless communication system of the wireless signal.

Technical Field

Various aspects of the present disclosure relate generally to wireless communication systems, and more particularly to initial frequency scanning for user equipment. Certain embodiments of the techniques discussed below may improve wireless system detection capabilities with reduced EARFCN uncertainty.

Background

Wireless communication networks have been widely deployed to provide various communication services such as voice, video, packet data, messaging, broadcast, and so on. These wireless networks may be multiple-access networks capable of supporting multiple users by sharing the available network resources. These networks, which are typically multiple-access networks, support communication for multiple users by sharing the available network resources.

A wireless communication network may include multiple base stations or node bs that can support communication for multiple User Equipment (UE). A UE may communicate with a base station via the downlink and uplink. The downlink (or forward link) refers to the communication link from the base stations to the UEs, and the uplink (or reverse link) refers to the communication link from the UEs to the base stations.

A base station may transmit data and control information to a UE on the downlink and/or may receive data and control information from a UE on the uplink. On the downlink, transmissions from a base station may encounter interference due to transmissions from neighbor base stations or transmissions from other wireless Radio Frequency (RF) transmitters. On the uplink, transmissions from a UE may encounter interference from uplink transmissions from other UEs or other wireless RF transmitters communicating with neighbor base stations. This interference may degrade performance on the downlink and uplink.

As the demand for mobile broadband access continues to increase, the more UEs accessing a long-distance wireless communication network, the more short-distance wireless systems deployed in a community, and the increased likelihood of network interference and congestion. Continuing to research and develop wireless technologies, not only can meet the growing demand for mobile broadband access, but also enhance and enhance the user's experience with mobile communications.

A User Equipment (UE) performs a Frequency Scan (FSCAN) when attempting initial acquisition. Power-based FSCAN may be limited by the signal-to-noise ratio (SNR). For example, for SNRs below-5 dB, FSCAN may fail and detection performance is poor even at 0dB, which makes power-based FSCAN unsuitable for UE mode B. In poor coverage, the UE in mode B searches each EARFCN to detect primary and secondary synchronization signals (PSS/SSS), which is very time consuming and computationally complex. Cyclic Prefix (CP) correlation can be used to enhance FSCAN, but FSCAN based on CP correlation has two major drawbacks. First, performance is very sensitive to a fraction of the LTE bandwidth acquired and the bandwidth of the target LTE system. Second, the number of potential EARFCNs for CP correlation after search is high.

Disclosure of Invention

The following presents a simplified summary of some aspects of the disclosure in order to provide a basic understanding of the discussed technology. This summary is not an extensive overview of all contemplated features of the disclosure, and is intended to neither identify key or critical elements of all aspects of the disclosure, nor delineate the scope of any or all aspects of the disclosure. Its sole purpose is to present some concepts of one or more aspects of the disclosure in a general form as a prelude to the more detailed description that is presented later.

In one aspect of the disclosure, a method of performing wireless communication includes: samples of received data are accumulated by a User Equipment (UE) over a maximum front-end bandwidth of the UE during an initial cell search. The method further comprises the following steps: partitioning the samples into smaller non-overlapping blocks of spectrum; and performing correlation-based detection on one or more of the smaller non-overlapping blocks. The method further comprises the following steps: the wireless communication system is detected based on a result of the detection based on the correlation.

In a further aspect of the disclosure, a wireless communication apparatus includes a computer processor and a memory coupled to the processor. The computer processor is configured to: samples of received data are accumulated by a User Equipment (UE) over a maximum front-end bandwidth of the UE during an initial cell search. The computer processor is additionally configured to: the samples are partitioned into smaller non-overlapping blocks of spectrum. The computer processor is further configured to perform correlation-based detection on one or more of the smaller non-overlapping blocks. The computer processor is further configured to: the wireless communication system is detected based on a result of the detection based on the correlation.

Other aspects, features and embodiments of the present invention will become apparent to those ordinarily skilled in the art upon review of the following description of specific, exemplary embodiments of the invention in conjunction with the accompanying figures. While features of the invention are discussed with respect to certain embodiments and figures below, all embodiments of the invention can include one or more of the advantageous features discussed herein. In other words, while one or more embodiments may be discussed as having certain advantageous features, one or more of these features may also be used in accordance with the various embodiments of the invention discussed herein. In a similar manner, although exemplary embodiments are discussed below as being device, system, or method embodiments, it should be understood that these exemplary embodiments can be implemented with a wide variety of devices, systems, and methods.

Drawings

A further understanding of the nature and advantages of the present disclosure may be realized by reference to the following drawings. In the drawings, similar components or features have the same reference numerals. In addition, various components of the same type may be distinguished by following the reference label by an underline and a second label that distinguishes among the similar components. If only the first reference label is used in the specification, the description is applicable to any one of the similar components having the same first reference label irrespective of the second reference label.

Fig. 1 is a block diagram illustrating details of a wireless communication system, according to some embodiments of the present disclosure.

Fig. 2 is a block diagram conceptually illustrating a design of a base station/gbb and a UE configured according to some embodiments of the present disclosure.

Fig. 3 is a block diagram illustrating UE Frequency Scanning (FSCAN) of Long Term Evolution (LTE) bands, according to some embodiments of the present disclosure.

Fig. 4 is a block diagram illustrating a scan based on Cyclic Prefix (CP) correlation, in accordance with some embodiments of the present disclosure.

Fig. 5 is a block diagram illustrating identification of EARFCN candidates as a result of a CP correlation-based scan, according to some embodiments of the present disclosure.

Fig. 6 is a block diagram illustrating issues regarding alignment of LTE system bandwidth with UE bandwidth, in accordance with some embodiments of the present disclosure.

Fig. 7 is a block diagram illustrating issues regarding size differences between LTE system bandwidth and UE bandwidth, in accordance with some embodiments of the present disclosure.

Fig. 8 is a block diagram illustrating a problem with EARFCN uncertainty, according to some embodiments of the present disclosure.

Fig. 9 is a graphical representation of CP correlation based peak detection according to some embodiments of the present disclosure.

Fig. 10 is a graphical representation of a Cumulative Distribution Function (CDF) demonstrating the effect of partial LTE acquisition, in accordance with some embodiments of the present disclosure.

Fig. 11 is a block diagram illustrating performing spectral partitioning using a hilbert transform by splitting a UE bandwidth sample into two equal halves, according to some embodiments of the disclosure.

Fig. 12 is a block diagram illustrating processing of the two equal halves by downsampling and rotation, according to some embodiments of the present disclosure.

Fig. 13 is a block diagram illustrating partitioning of a UE 5MHz bandwidth spectrum in a binary tree fashion, according to some embodiments of the present disclosure.

Fig. 14 is a block diagram illustrating partitioning of a UE 20MHz bandwidth spectrum in a binary tree fashion, according to some embodiments of the present disclosure.

Fig. 15 is a graphical representation of a CDF exhibiting performance degradation due to frequency band splitting, according to some embodiments of the present disclosure.

Fig. 16 is a graphical representation of a CDF demonstrating the improvement in detectability of a wireless system in the left half of a frequency band due to frequency band segmentation, in accordance with some embodiments of the present disclosure.

Fig. 17 is a block diagram illustrating example blocks of a frequency bin splitting process for enhanced detection, in accordance with some embodiments of the present disclosure.

Fig. 18 is a block diagram illustrating example blocks of a frequency band segmentation process for reducing EARFCN uncertainty, according to some embodiments of the present disclosure.

Fig. 19 is a block diagram illustrating example blocks of an initial frequency scanning process in accordance with some embodiments of the present disclosure.

Fig. 20 is a block diagram illustrating a wireless communication device according to some embodiments of the present disclosure.

Detailed Description

The detailed description set forth below in connection with the appended drawings is intended as a description of various possible configurations only and is not intended to limit the scope of the present disclosure. Rather, the specific embodiments include specific details for a thorough understanding of the present invention. It will be apparent to one of ordinary skill in the art that these specific details are not required in every case, and in some instances, well-known structures and components are shown in block diagram form in order to facilitate a clear presentation.

The present disclosure relates generally to providing communication between or participating in communication between two or more wireless devices in one or more wireless communication systems (which may also be referred to as wireless communication networks). In various embodiments, the techniques and apparatus may be used in wireless communication networks such as: code Division Multiple Access (CDMA) networks, Time Division Multiple Access (TDMA) networks, Frequency Division Multiple Access (FDMA) networks, Orthogonal FDMA (OFDMA) networks, single-carrier FDMA (SC-FDMA) networks, Long Term Evolution (LTE) networks, global system for mobile communications (GSM) networks, and other communication networks. As described herein, the terms "network" and "system" may be used interchangeably depending on the particular context.

For example, a CDMA network may implement a radio technology such as Universal Terrestrial Radio Access (UTRA), CDMA2000, and so on. UTRA includes wideband CDMA (W-CDMA) and Low Chip Rate (LCR). CDMA2000 covers IS-2000, IS-95 and IS-856 standards.

A TDMA network may, for example, implement a radio technology such as GSM. The 3GPP defines a standard for GSM EDGE (enhanced data rates for GSM evolution) Radio Access Networks (RAN), also known as GERAN. GERAN is the radio component of GSM/EDGE and the network connecting base stations (e.g., the Ater and Abis interfaces) and base station controllers (a interfaces, etc.). The radio access network represents the component of a GSM network through which telephone calls and packet data are routed to and from the Public Switched Telephone Network (PSTN) and the internet, and to and from user handsets (also known as user terminals or User Equipment (UE)). The network of the mobile telephone operator may comprise one or more GERANs, which in the case of a UMTS/GSM network may be coupled with a Universal Terrestrial Radio Access Network (UTRAN). The operator network may also include one or more LTE networks and/or one or more other networks. The various different network types may use different Radio Access Technologies (RATs) and Radio Access Networks (RANs).

An OFDMA network may, for example, implement radio technologies such as evolved UTRA (E-UTRA), IEEE 802.11, IEEE 802.16, IEEE 802.20, flash-OFDM, and so on. UTRA, E-UTRA and GSM are part of the Universal Mobile Telecommunications System (UMTS). Specifically, LTE is a release of UMTS that employs E-UTRA. UTRA, E-UTRA, GSM, UMTS and LTE are described in documents provided by an organization named "third generation partnership project" (3GPP), and cdma2000 is described in documents from an organization named "third generation partnership project 2" (3GPP 2). These various radio technologies and standards are known or under development. For example, the third generation partnership project (3GPP) is directed to a collaboration between the telecommunications union group that specifies the globally applicable third generation (3G) mobile phone specification. The 3GPP Long Term Evolution (LTE) is a 3GPP project aimed at improving the Universal Mobile Telecommunications System (UMTS) mobile phone standard. The 3GPP may specify specifications for next generation mobile networks, mobile systems and mobile devices.

For clarity of explanation, certain aspects of these apparatus and techniques are described below with reference to exemplary LTE embodiments or LTE-centric approaches, and LTE terminology may be used as an illustrative example in portions of the following description; however, the description is not intended to be limited to LTE applications. Indeed, the present disclosure relates to shared access to wireless spectrum between networks using different radio access technologies or radio air interfaces.

Further, it should be understood that, in operation, a wireless communication network adapted according to the concepts herein may operate in any combination of licensed or unlicensed spectrum, depending on load and availability. Thus, it will be apparent to those of ordinary skill in the art that the systems, apparatus, and methods described herein may be applied to other communication systems and applications in addition to the specific examples provided.

While aspects and embodiments have been described herein through the illustration of some examples, those of ordinary skill in the art will appreciate that additional implementations and use cases may be implemented in many different arrangements and scenarios. The innovations described herein may be implemented across a number of different platform types, devices, systems, shapes, sizes, packaging arrangements. For example, embodiments and/or uses may be implemented by integrated chip embodiments and/or other non-modular component based devices (e.g., end-user devices, vehicles, communication devices, computing devices, industrial devices, retail/purchase devices, medical devices, AI-enabled devices, etc.). While some examples may or may not be specific to use cases or applications, a wide variety of applicability of the described innovations may occur. Implementations may range from chip-level or modular components to non-modular, non-chip-level implementations, and may also be aggregated, distributed, or OEM devices or systems incorporating one or more of the described aspects. In some practical settings, a device incorporating the described aspects and features may also necessarily include other components and features for implementing and practicing the claimed and described embodiments. The innovations described herein may be practiced in a wide variety of implementations having different sizes, shapes and configurations, including large/small devices, chip-level components, multi-component systems (e.g., RF chains, communication interfaces, processors), distributed arrangements, end-user devices, and so forth.

Fig. 1 illustrates a wireless network 100 for communication in accordance with some embodiments. Although a discussion of the techniques of this disclosure is provided with respect to an LTE-a network (shown in fig. 1), this is for illustration purposes only. The principles of the disclosed technology may also be used in other network deployments, including fifth generation (5G) networks. As will be appreciated by those of ordinary skill in the art, the components presented in fig. 1 may have related counterparts in other network arrangements, including, for example, cellular network arrangements and non-cellular network arrangements (e.g., device-to-device or peer-to-peer or ad hoc network arrangements, etc.).

Returning to fig. 1, wireless network 100 includes a plurality of base stations, which may include, for example, evolved node bs (enbs) or G node bs (gnbs). These may be referred to as gnbs 105. The gNB may be a station that communicates with the UE and may also be referred to as a base station, a node B, an access point, etc. Each gNB 105 may provide communication coverage for a particular geographic area. In 3GPP, the term "cell" can refer to this particular geographic coverage area of a gNB, and/or a gNB subsystem serving this coverage area, depending on the context in which the term is used. In implementations of wireless network 100 herein, the gNB 105 may be associated with the same operator or different operators (e.g., wireless network 100 may include multiple operator wireless networks) and may provide wireless communication using one or more frequencies (e.g., one or more frequency bands in licensed spectrum, unlicensed spectrum, or a combination thereof) that are the same frequency as neighboring cells.

The gNB may provide communication coverage for a macro cell or a small cell (e.g., a pico cell or a femto cell) and/or other types of cells. Typically, a macro cell covers a relatively large geographic area (e.g., several kilometers in radius) and may allow unrestricted access by UEs with service subscriptions with the network provider. In general, small cells, such as pico cells, cover a relatively small geographic area and allow unrestricted access with UEs with service subscriptions with the network provider. Furthermore, small cells, such as femtocells, typically cover relatively small geographic areas (e.g., homes), which provide restricted access to UEs having an association with the femtocell (e.g., UEs in a Closed Subscriber Group (CSG), UEs for users in a home, etc.) in addition to unrestricted access. The gbb for a macro cell may be referred to as a macro gbb. A gNB for a small cell may be referred to as a small cell gNB, pico gNB, femto gNB, or home gNB. In the example shown in fig. 1, the gnbs 105a, 105b, and 105c are macro gnbs for the macro cells 110a, 110b, and 110c, respectively. The gnbs 105x, 105y, and 105z are small cell gnbs, which may include pico or femto gnbs for providing services to small cells 110x, 110y, and 110z, respectively. The gNB may support one or more (e.g., two, three, four, etc.) cells.

Wireless network 100 may support synchronous or asynchronous operation. For synchronous operation, the gnbs may have similar frame timing, and transmissions from different gnbs are approximately aligned in time. For asynchronous operation, the gnbs may have different frame timing, and transmissions from different gnbs may not be aligned in time. In some scenarios, the network may be enabled or configured to handle dynamic switching between synchronous or asynchronous operations.

UEs 115 are dispersed throughout wireless network 100, and each UE may be stationary or mobile. It should be appreciated that while in the standards and specifications promulgated by the third generation partnership project (3GPP), a mobile device is often referred to as User Equipment (UE), one of ordinary skill in the art may also refer to such a device as a Mobile Station (MS), a subscriber station, a mobile unit, a subscriber unit, a wireless unit, a remote unit, a mobile device, a wireless communications device, a remote device, a mobile subscriber station, an Access Terminal (AT), a mobile terminal, a wireless terminal, a remote terminal, a handset, a terminal, a user agent, a mobile client, a client, or some other suitable terminology. Within this document, a "mobile" device or UE need not have mobility capabilities and may be stationary. Some non-limiting examples of mobile devices, for example, may include embodiments of one or more of the UEs 115, including mobile stations, cellular (cell) phones, smart phones, Session Initiation Protocol (SIP) phones, laptops, Personal Computers (PCs), notebooks, netbooks, smart books, tablets, and Personal Digital Assistants (PDAs). The mobile device may also be an "internet of things" (IoT) device, such as an automobile or other vehicle, a satellite radio, a Global Positioning System (GPS) device, a logistics controller, a drone, a multi-axis aircraft, a quadcopter, a smart energy or security device, a solar panel or solar array, municipal lighting, water, or other infrastructure; industrial automation and enterprise equipment; consumer and wearable devices, such as glasses, wearable cameras, smart watches, health or fitness trackers, mammalian implantable devices, gesture tracking devices, medical devices, digital audio players (e.g., MP3 players), cameras, game consoles, and so forth; and digital home or smart home devices such as home audio, video and multimedia devices, appliances, sensors, vending machines, smart lighting, home security systems, smart meters, and the like. A mobile device, such as UE 115, can communicate with a macro gNB, pico gNB, femto gNB, relay, and so on. In fig. 1, the lightning bolt (e.g., communication link 125) indicates a wireless transmission between the UE and a serving gNB (where the serving gNB is a gNB designated to serve the UE on the downlink and/or uplink), or a desired transmission between the gnbs. While backhaul communication 134 is shown as a wired backhaul communication that may occur between the gnbs, it should be understood that backhaul communication may additionally or alternatively be provided through wireless communication.

Fig. 2 shows a block diagram of a design of a base station/gNB 105 and a UE 115. These devices may be one of the base stations/gbbs in fig. 1 and one of the UEs in fig. 1. For the restricted association scenario (as mentioned above), the gNB 105 may be the small cell gNB 105z in fig. 1 and the UE 115 may be UE 115z, and to access the small cell gNB 105z, the UE 115z will be included in the accessible UE list for the small cell gNB 105 z. The gNB 105 may also be some other type of base station. The gNB 105 may be equipped with antennas 234a through 234t, while the UE 115 may be equipped with antennas 252a through 252 r.

At the gNB 105, a transmit processor 220 may receive data from a data source 212 and control information from a controller/processor 240. The control information may be for a Physical Broadcast Channel (PBCH), a Physical Control Format Indicator Channel (PCFICH), a physical hybrid ARQ indicator channel (PHICH), a Physical Downlink Control Channel (PDCCH), and the like. The data may be for a Physical Downlink Shared Channel (PDSCH), and so on. Transmit processor 220 may process (e.g., encode and symbol map) the data and control information to obtain data symbols and control symbols, respectively. Transmit processor 220 may also generate reference symbols, e.g., for a Primary Synchronization Signal (PSS), a Secondary Synchronization Signal (SSS), and a cell-specific reference signal (CRS). A Transmit (TX) multiple-input multiple-output (MIMO) processor 230 may perform spatial processing (e.g., precoding) on the data symbols, the control symbols, and/or the reference symbols, if applicable, and may provide output symbol streams to the Modulators (MODs) 232a through 232 t. Each modulator 232 may process a respective output symbol stream (e.g., for OFDM, etc.) to obtain an output sample stream. Each modulator 232 may additionally or alternatively process (e.g., convert to analog, amplify, filter, and upconvert) the output sample stream to obtain a downlink signal. Downlink signals from modulators 232a through 232t may be transmitted via antennas 234a through 234t, respectively.

At the UE 115, antennas 252a through 252r may receive downlink signals from the gNB 105 and provide received signals to demodulators (DEMODs) 254a through 254r, respectively. Each demodulator 254 may condition (e.g., filter, amplify, downconvert, and digitize) a respective received signal to obtain input samples. Each demodulator 254 may further process the input samples (e.g., for OFDM, etc.) to obtain received symbols. A MIMO detector 256 may obtain received symbols from all demodulators 254a through 254r, perform MIMO detection on the received symbols (if applicable), and provide detected symbols. A receive processor 258 may process (e.g., demodulate, deinterleave, and decode) the detected symbols, provide decoded data for the UE 115 to a data sink 260, and provide decoded control information to a controller/processor 280.

On the uplink, at UE 115, a transmit processor 264 may receive data (e.g., for the PUSCH) from a data source 262, receive control information (e.g., for the PUCCH) from a controller/processor 280, and process the data and control information. The transmit processor 264 may also generate reference symbols for a reference signal. The symbols from transmit processor 264 may be precoded by a TX MIMO processor 266 if applicable, further processed by modulators 254a through 254r (e.g., for SC-FDM, etc.), and transmitted to the gNB 105. At the gNB 105, the uplink signals from the UE 115 may be received by antennas 234, processed by demodulators 232, detected by a MIMO detector 236 (if applicable), and further processed by a receive processor 238 to obtain the decoded data and control information transmitted by the UE 115. Processor 238 may provide the decoded data to a data sink 239 and the decoded control information to controller/processor 240.

Controllers/processors 240 and 280 may direct operation at gNB 105 and UE 115, respectively. Controller/processor 240 and/or other processors and modules at gNB 105 and/or controller/processor 280 and/or other processors and modules at UE 115 may perform or direct the performance of various processes for implementing the techniques described herein, e.g., the processes shown in fig. 10-19 and/or other processes for the techniques described herein. Memories 242 and 282 may store data and program codes for the gNB 105 and UE 115, respectively. A scheduler 244 may schedule UEs for data transmission on the downlink and/or uplink.

Fig. 3-10 provide details regarding challenges caused by initial frequency scanning by a UE, such as UE 115. The UE performs a Frequency Scan (FSCAN) in an attempt to initially acquire the wireless communication system. Power-based FSCAN may be limited by the signal-to-noise ratio (SNR). For example, FSCAN may fail when the SNR is below-5 dB and the detection performance is poor even at 0dB, which makes power-based FSCAN unsuitable for UE mode B. In poor coverage, the UE in mode B searches each EARFCN to detect primary and secondary synchronization signals (PSS/SSS), which is very time consuming and computationally complex. Cyclic Prefix (CP) correlation can be used to enhance FSCAN, but FSCAN based on CP correlation has two major drawbacks. First, performance is very sensitive to a fraction of the LTE bandwidth acquired and the bandwidth of the target LTE system. Second, the number of potential EARFCNs for CP correlation after search is high.

Referring to fig. 3, a wireless communication system, such as an LTE system 300, occupies a portion of a frequency band (such as an LTE frequency band 302). The true EARFCN 304 may, for example, correspond to a center frequency of the LTE system 300. The objective of FSCAN is to find the real EARFCN 304 in the shortest possible time. To this end, the UE scans the LTE band 302 by dividing the LTE band into a minimum number of possible sub-bands. Typically, the UE bandwidth 306 is set to the maximum supported bandwidth of the UE's radio modem. For example, for some UE modems, the maximum supported bandwidth may be 20 MHz. Alternatively, for other modems designed for internet of things (IoT) applications, the maximum supported bandwidth may be 5MHz, which would require the UE to scan the LTE band 302 using a 5MHz bandwidth.

Referring to fig. 4, FSCAN based on CP correlation is a new application of CP correlation. The LTE signal consists of OFDM symbols 400 defined by cyclic prefixes 402A and 402B. CP correlation-based FSCAN techniques exploit this inherent correlation present in LTE signals and perform auto-correlation on a certain number of accumulated samples over each UE bandwidth to detect CP correlation. If no CP correlation is detected, there is no need to search for EARFCN in the current portion of the band, resulting in a final time saving. As shown in fig. 5, the method may narrow down potential EARFCN candidates to several UE bandwidths 500A and 500B.

Referring to fig. 6, a problem with the alignment of the LTE system bandwidth with the UE bandwidth may occur. This drawback of CP correlation based FSCAN arises from the sensitivity to the bandwidth of the deployed LTE system and the portion of the LTE system that is acquired. In particular, whenever the captured portion of the LTE system is reduced, the detectability of the LTE system is reduced. For example, when the LTE system 600A is aligned with the UE bandwidth 602A, most or all of the LTE system 600A is captured within samples accumulated over the UE bandwidth 602A. However, when the LTE system 600B is not aligned with either the UE bandwidth 602B or 602C, then only a portion of the LTE system 600B is acquired in each UE bandwidth 602B and 602C. As a result, the accumulated samples corresponding to each of the UE bandwidths 602B and 602C exhibit a reduction in the associated energy captured, as well as unwanted interference from samples at locations where no LTE system is present. As shown in fig. 7, a similar problem exists when the LTE system bandwidth 700 is significantly smaller than the UE bandwidth 702.

Turning now to fig. 8, other drawbacks of the FSCAN based on CP correlation stem from the problem with EARFCN uncertainty. For example, even though FSCAN based on CP correlation provides gain by eliminating a large portion of the LTE band (no LTE system at these locations), there is still a significant degree of EARFCN uncertainty. In the example of the LTE system 800 being misaligned with the UE bandwidths 802A and 802B, the true EARFCN may be anywhere within the UE bandwidths 802A and 802B. For 5MHz, 10MHz and 20MHz UE bandwidths, there are 45, 90 and 180 EARFCNs per UE bandwidth, respectively. The computational time required to scan all of these EARFCNs to locate the true EARFCNs is too long. Furthermore, EARFCN uncertainty increases further with false alarms, which can be expected under low SNR conditions.

Referring to fig. 9, a CP accumulation buffer bcorr (n) may be used to perform CP correlation-based peak detection to accumulate CP correlation values through autocorrelation and coherently combine the correlation values over a specified duration (T). For example, for a UE bandwidth of 5MHz, n may be the sameThe buffer bcorr (n) is defined by 0,1, …, 548. Performance metrics

And may be decided according to the following conditions:

1,z≥

0,z<

among these are detection thresholds. This CP correlation based technique is expected to detect-15 dB LTE signals and can increase the correlation gain by increasing the acquisition time (T).

Turning to fig. 10, the Cumulative Distribution Function (CDF) demonstrates the effect of partial LTE acquisition. CDF is plotted along the ordinate axis and the performance matrix z is plotted along the abscissa. For correct detection, the detection threshold must be able to separate CDFs in LTE and non-LTE cases. Two cases are considered and compared to CDF 1000 without LTE. Case 1 considers the case where the full LTE system is acquired in the UE bandwidth, while only half of the LTE system is acquired in case 2. The CDF 1004 of case 1 is significantly different from the CDF 1000 without LTE, while the CDF 1002 of case 2 exhibits significant overlap with the CDF 1000 without LTE. As mentioned previously, one way to enhance detection is to increase the capture time, but this increase can result in additional time due to the accumulation of additional samples. As also previously mentioned, even if an LTE system is detected, post-processing is still required for the erroneous EARFCN corresponding to the free portion of the bandwidth, which in turn incurs additional time and computational costs.

Fig. 11-20 provide details related to proposed solutions that improve detection and/or reduce EARFCN uncertainty without incurring the above-described penalties due to increased acquisition time and/or post-processing to eliminate excessive erroneous EARFCNs. In principle, the solution proposed below is described with reference to the UE bandwidth of 5MHz and the use of CP correlation based detection. However, it is contemplated that other UE bandwidths and/or other correlation-based detection techniques may be employed. For example, another potential correlator is based on CRS autocorrelation. However, CRS-based correlators are sensitive to Frequency Offset (FO) errors and high doppler fading. In contrast, a CP-based correlator is robust to both FO and high doppler and is therefore currently preferred.

The solution disclosed herein implements frequency binning to address the issue of CP correlation based FSCAN. This solution effectively increases the detection probability and narrows down the potential EARFCNs to a small number. This basic solution involves: the spectrum is divided into smaller blocks (or sub-bands) by accumulating samples over the maximum UE bandwidth and splitting samples with smaller non-overlapping bandwidths to make an accurate decision over the smaller blocks of spectrum. This division avoids separate accumulation of samples for smaller blocks of spectrum.

In some embodiments, described in detail below with respect to fig. 11-16, the spectrum partitioning is performed by subdividing the spectrum into a number of levels in a binary tree fashion, where the number of levels is selected to ensure that all smallest blocks of spectrum at the lowest level of the tree have a bandwidth equal to the minimum supported bandwidth. At each level, the bandwidth is divided into two halves (the positive and negative halves) using a hilbert transform. For each half, downsampling and rotation are performed, and CP correlation-based decisions are made at each level to achieve maximum performance advantage.

In other embodiments, described in detail below with reference to fig. 17, the samples are partitioned into blocks in response to failing to make a strong decision on the detection of the wireless signal in the samples, and further partitioning of any block is performed in response to determining that a strong decision cannot be made on the detection of the wireless signal in the block. Determining that a strong decision cannot be made for the detection of the wireless signal if z is less than a detection threshold, where z is equal to the CP accumulation buffer Bcor (n) for CPA performance metric of (a).

In other embodiments, described in detail below with reference to fig. 18, the samples are segmented to accurately locate the wireless system of the wireless signal in response to detecting the wireless signal in the sample. Further division of any blocks is also performed in response to detecting a wireless signal in a blockAnd (6) cutting. Determining that a wireless signal is present if z is greater than a detection threshold, wherein z is equal to the CP accumulation buffer Bcor (n)

A performance metric of (a).

Referring to fig. 11, spectral partitioning is performed by splitting a 5MHz UE bandwidth sample 1102 into two equal halves 1104 and 1106 using a hilbert transform 1100. In this example, for other modems, the UE is configured with a 5MHz front end bandwidth of 5MHz, with a sampling rate of 7.68MHz and a fast fourier transform size NFFT of 512. As noted above, it is envisioned that other UE front-end bandwidths may be used.

Referring to fig. 12, each of two equal halves 1104 and 1106 may be processed by downsampling to yield downsampled halves 1200 and 1202, and these downsampled halves 1200 and 1202 may be rotated to yield downsampled and rotated halves 1204 and 1206. For example, the two halves 1104 and 1106 may be downsampled twice such that the sampling rate of the downsampled signal matches the UE bandwidth of 3 MHz. Further, the downsampled half 1200 may be rotated clockwise by 1.125MHz, or 2.25/7.68 of the normalized frequency. Also, the downsampled half 1202 may be rotated counter-clockwise by 1.125MHz, or a normalized frequency of 2.25/7.68. This processing makes the downsampled and rotated halves 1204 and 1206 suitable for further processing by CP correlation based detection.

Referring to fig. 13, the partitioning and processing of the UE bandwidth samples 1102 and the downsampled and rotated halves 1204 and 1206 may continue to be performed in a binary tree fashion to result in a tree with a number of levels, where the leaves 1300, 1302, 1304, and 1306 at the lowest level of the tree cannot be further partitioned, resulting in no half with bandwidth below the minimum supported bandwidth. For a UE bandwidth of 5MHz, it is sufficient to perform the partitioning into at most three tiers, since the bandwidth of the smallest spectrum block is equal to the minimum supported LTE bandwidth of 1.4 MHz. Up to five levels of partitioning may be performed for a UE with a front-end bandwidth of 20 MHz. Therefore, the method can reliably detect the target LTE system deployed with any supported bandwidth.

Referring to fig. 14, the partitioning of the UE 20MHz bandwidth spectral samples 1400 may be performed in a binary tree fashion, using a hilbert transform 1402, downsampling and rotation processes 1404 and 1406 between each level to yield downsampled and rotated halves 1408 and 1410. In this example, the UE is configured to have a front-end bandwidth of 20MHz, a sampling rate of 30.72MHz, and a fast Fourier transform size NFFT of 2048. In this case, up to five levels of partitioning may be performed such that the leaves of the tree result with the bandwidth of the spectrum block equal to the minimum supported LTE bandwidth of 1.4 MHz.

Turning to fig. 15, four CDFs exhibit the potential for performance degradation due to frequency band splitting. CDF is plotted along the ordinate axis and the performance matrix z is plotted along the abscissa. For correct detection, the detection threshold must be able to separate CDFs in LTE and non-LTE cases. The CDF 1500 without LTE is drawn with the full band CDF 1502 and the left and right halves of CDFs 1504 and 1506 at level two. The full-band CDF 1502 is significantly different from the CDF 1500 without LTE, while the performance of the left and right half CDFs 1504 and 1506 is degraded compared to the full-band CDF 1502. This performance degradation is due to the division of the associated energy between the two halves. Therefore, it is presently preferred that CP correlation-based detection is performed at each frequency band or frequency band portion of each tier.

Turning to fig. 16, four CDFs demonstrate the potential for improved performance due to frequency band splitting. CDF is plotted along the ordinate axis and the performance matrix z is plotted along the abscissa. For correct detection, the detection threshold must be able to separate CDFs in LTE and non-LTE cases. The CDF1600 without LTE is plotted with the CDF 1602 full band, the CDF 1604 in the right half of the band at level two, and the CDF 1606 in the left half of the band at level two. The full band CDF 1602 exhibits significant overlap with the CDF1600 without LTE, and in the left half of the band, detectability is improved. The CDF 1606 in the left half of the band is substantially separated from the CDF1600 without LTE compared to the CDF1600 in the full band. Thus, the probability of detection in the left half of the band is increased due to the segmentation. In contrast, the CDF 1604 for the right half of the band is fully merged with the CDF1600 without LTE, eventually identifying the idle portion of the spectrum and reducing EARFCN uncertainty.

As described in detail above with respect to fig. 11-16, the proposed binary tree approach is helpful for both aspects of FSCAN. For example, the detection probability is improved. In particular, spectrum partitioning can improve detection probability when the target LTE system bandwidth is less than the UE front-end bandwidth of the maximum supported bandwidth of the modem configured as a UE. Detection enhancements may also occur when the UE acquires only a portion of the LTE system. In addition to improving detection probability, spectrum segmentation may also reduce EARFCN uncertainty. In particular, the frequency band partitioning may further narrow the EARFCN search space by effectively rejecting the free portion of the frequency band. As described above, since the division of correlation energy between spectrum blocks may cause performance degradation, it is suggested that CP correlation-based detection be performed at each level. However, doing so increases computational complexity. Therefore, to reduce complexity, some additional methods are described below with reference to fig. 17 and 18. These methods may be selectively used to enhance detection or reduce EARFCN uncertainty, depending on UE requirements.

Referring to fig. 17, a band splitting process may be employed to enhance detection only when a strong decision cannot be made as to the presence of LTE signals in the respective band portion 1700 being considered. For example, the frequency band portion 1700 may be a full UE front-end bandwidth or a downsampled and rotated block thereof. CP correlation based detection may be performed on the band portion 1700 and at block 1702, a determination is made whether a strong peak is detected based on whether the resulting performance metric z is greater than or equal to a detection threshold. If a strong peak is detected at block 1702, no further partitioning need be performed for the band portion 1700. However, if no strong peak is detected in block 1702, the bin portion 1700 may be segmented and the halves downsampled and rotated to produce additional bin portions 1704 and 1706. These additional band portions 1704 and 1706 may then be evaluated by CP correlation-based detection and, if they are still large enough to withstand segmentation (without producing blocks of too small a size), they may be subjected to the same selective band segmentation process as the band portion 1700. Thus, frequency band splitting may be selectively performed for conditions of narrow LTE systems or partial LTE acquisition, providing gain (especially under low SNR conditions) in such scenarios. The goal of this approach is to increase the detection probability, which is highly desirable under low SNR conditions.

Referring to fig. 18, a frequency band splitting procedure may be employed to reduce EARFCN uncertainty, which may be helpful in relatively high SNR scenarios where portions of the LTE signal may also be detected. In this approach, the band segmentation may be performed only if a strong decision can be made on the presence of LTE signals in the respective band portion 1700 being considered. For example, the band portion 1800 may be the full UE front-end bandwidth or a downsampled and rotated block thereof. CP correlation based detection may be performed on the band portion 1800 and a determination is made at block 1802 as to whether a strong peak has not been detected based on whether the resulting performance metric z is less than a detection threshold. If no strong peak is detected, no further segmentation is performed on the frequency band portion 1800 under evaluation. However, if a strong peak is detected at block 1802, the frequency band portion 1800 may be split and the halves downsampled and rotated to produce additional frequency band portions 1804 and 1806. These additional band portions 1804 and 1806 may then be evaluated by CP correlation-based detection and, if they are still large enough to withstand segmentation (without producing blocks of too small a size), they may be subjected to the same selective band segmentation process as band portion 1800. In this way, frequency band segmentation may be performed to accurately locate the LTE system, thereby reducing potential EARFCNs.

Referring to fig. 19, the method of wireless communication includes: may be performed by the UE, the relay node, or another wireless communication device performing the initial frequency scanning procedure. Beginning at block 1900, the method includes: the method includes accumulating, by a UE, samples of received data over a maximum front-end bandwidth of the UE during an initial cell search. Processing may proceed from block 1900 to block 1902.

At block 1902, the UE may partition the samples into smaller, non-overlapping blocks of spectrum. It is contemplated that block 1902 may include: at least one of the smaller non-overlapping blocks is further partitioned into smaller non-overlapping blocks. In some implementations, block 1902 may include: the spectrum is subdivided in a binary tree fashion with a certain number of levels, where at each of these levels the bandwidth is divided into two halves. It is also contemplated that the subdivision of the bandwidth may be achieved by performing a hilbert transform. Additionally, block 1902 may include: at each of these levels, CP correlation detection is performed on each of the smaller non-overlapping blocks, and/or at least one of the two halves is processed by downsampling and rotating the at least one of the two halves. Further, block 1902 may include: the number of levels is chosen to ensure that all the smallest spectral blocks at the lowest level have a respective bandwidth equal to the minimum supported bandwidth (e.g., 1.4 MHz).

Alternatively or in addition to subdividing the spectrum in a binary tree, block 1902 may include: the sample is partitioned into two or more smaller non-overlapping blocks in response to an inability to make a strong decision on the detection of the wireless signal in the sample. In this embodiment, block 1902 may include: in response to determining that a strong decision cannot be made for detection of a wireless signal in at least one of the smaller non-overlapping blocks, further partitioning the at least one of the smaller non-overlapping blocks into smaller non-overlapping blocks. It is contemplated that determining that a strong decision cannot be made for detection of a wireless signal at block 1902 may correspond to determining that z is less than a detection threshold, where z is equal to a Cyclic Prefix (CP) accumulation buffer bcorr (n)

A performance metric of (a).

As a further alternative or in addition to subdividing the spectrum in a binary treeIn addition, block 1902 may include: in response to detecting a wireless signal in a sample, the sample is partitioned into two or more smaller non-overlapping blocks. In this embodiment, block 1902 may include: in response to detecting a wireless signal in at least one of the smaller non-overlapping blocks, the at least one of the smaller non-overlapping blocks is further partitioned into smaller non-overlapping blocks. It is contemplated that detecting the presence of a wireless signal may correspond to determining z is greater than a detection threshold, where z is equal to a Cyclic Prefix (CP) accumulation buffer bcorr (n) for a CPA performance metric of (a). In this embodiment, block 1902 may be performed to segment samples to accurately locate the wireless communication system for the wireless signal. Processing may proceed from block 1902 to block 1904.

At block 1904, the UE may perform correlation-based detection on one or more of the smaller non-overlapping blocks. For embodiments involving subdividing the spectrum in a binary tree fashion in block 1902, block 1904 may include: at each level of the tree, a correlation-based detection is performed for each spectral block. For those implementations involving a determination at block 1902 that a strong decision cannot be made for detection of a wireless signal or a segmentation of a sample into blocks in response to detection of a wireless signal, the correlation-based detection results performed in block 1904 may be used in block 1902 to make a corresponding decision. Thus, it is contemplated that processing may return to block 1902 in a recursive manner until it is determined that segmentation is no longer being performed. Processing may proceed from block 1904 to block 1906.

At block 1906, the UE may detect the wireless communication system based on a result of the correlation-based detection. For example, the UE may select the block or bandwidth portion that exhibits the highest performance metric z and search the EARFCN for that block to find the true EARFCN for the wireless communication system. After block 1906, the UE may perform other procedures (such as synchronization and/or access to the wireless system), as will be apparent to one of ordinary skill in the art.

Turning to fig. 20, as described above, a UE 2000, such as UE 115 (see fig. 2), may have a controller/processor 280, a memory 282, and antennas 252a through 252 r. The UE 2000 may also have radios 2001 a-2001 r, which radios 2001 a-2001 r include other components also described above with reference to fig. 2. The memory 282 of the UE 2000 stores algorithms for configuring the processor/controller 280 to perform the processes described above in fig. 11-19.

As previously described, the algorithms stored by the memory 282 configure the processor/controller 280 to perform procedures related to performing an initial frequency scan by the UE 2000. For example, the sample accumulator 2002 configures the controller/processor 280 to perform operations including accumulating samples in a buffer over the UE front-end bandwidth in any manner previously described. In addition, a sample divider 2003 configures the controller/processor 280 to perform operations including dividing samples into smaller non-overlapping blocks in any of the manners previously described. Moreover, the correlation-based detector 2004 configures the controller/processor 280 to perform operations including performing correlation-based detection on the accumulated samples and/or portions thereof in any of the manners previously described. Further, wireless system detector 2005 configures controller/processor 280 to perform operations including detecting a wireless system based on correlation-based detection results in any of the manners previously described.

Those of skill in the art would understand that information and signals may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips that may be referenced throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

The functional blocks and modules described herein (e.g., in fig. 2 and 11-20) may comprise processors, electronics devices, hardware devices, electronics components, logic circuits, memories, software codes, firmware codes, etc., or any combination thereof.

Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure. Skilled artisans will also readily appreciate that the sequence or combination of components, methods, or interactions described herein is merely exemplary and that the components, methods, or interactions of the various aspects of the present disclosure may be combined or performed in a manner different than those illustrated and described herein.

A general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein may be used to implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a number of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.

The steps of a method or algorithm described in connection with the disclosure herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium may be coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In the alternative, the processor and the storage medium may reside as discrete components in a user terminal.

In one or more exemplary designs, the functions described herein may be implemented in hardware, software, firmware, or any combination thereof. When implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. Computer-readable storage media can be any available media that can be accessed by a general purpose or special purpose computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code means in the form of instructions or data structures and that can be accessed by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor. Also, a connection may be properly termed a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, or Digital Subscriber Line (DSL), then the coaxial cable, fiber optic cable, twisted pair, or DSL are included in the definition of medium. Disk and disc, as used herein, includes Compact Disc (CD), laser disc, optical disc, Digital Versatile Disc (DVD), hard disk, solid state disc, and blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

As used herein (including in the claims), when the term "and/or" is used in a list of two or more items, it means that any one of the listed items can be used alone, or any combination of two or more of the listed items can be used. For example, if a complex is described as containing component A, B and/or C, the complex can contain only A; only B is contained; only C is contained; a combination of A and B; a combination of A and C; a combination of B and C; or a combination of A, B and C. Further, as used herein (including in the claims), the use of "or" in a list of items prefaced by "at least one of" indicates a separate list, such that, for example, a list of "A, B or" at least one of C "means: any one of A or B or C or AB or AC or BC or ABC (i.e., A and B and C), or any combination thereof.

The previous description is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the disclosure is not intended to be limited to the examples and designs described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.